| 2026 | AAAI | Forecasting Clinical Risk from Textual Time Series: Structuring Narratives for Temporal AI in Healthcare. | Shahriar Noroozizadeh, Sayantan Kumar, Jeremy C. Weiss |
| 2024 | PAKDD | Using Multimodal Data to Improve Precision of Inpatient Event Timelines. | Gabriel Frattallone-Llado, Juyong Kim, Cheng Cheng, Diego Salazar, Smitha Edakalavan, Jeremy C. Weiss |
| 2023 | AAAI | Censored Fairness through Awareness. | Wenbin Zhang, Tina Hernandez-Boussard, Jeremy C. Weiss |
| 2023 | ECAI | Individual Fairness Under Uncertainty. | Wenbin Zhang, Zichong Wang, Juyong Kim, Cheng Cheng, Thomas Oommen, Pradeep Ravikumar, Jeremy C. Weiss |
| 2022 | AAAI | Longitudinal Fairness with Censorship. | Wenbin Zhang, Jeremy C. Weiss |
| 2022 | AMIA | Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19. | Helen Zhou, Cheng Cheng, Kelly J. Shields, Gursimran Kochhar, Tariq Cheema, Zachary C. Lipton, Jeremy C. Weiss |
| 2022 | EMNLP | AnEMIC: A Framework for Benchmarking ICD Coding Models. | Juyong Kim, Abheesht Sharma, Suhas Shanbhogue, Jeremy C. Weiss, Pradeep Ravikumar |
| 2021 | AIME | Disentangled Hyperspherical Clustering for Sepsis Phenotyping. | Cheng Cheng, Jason N. Kennedy, Christopher W. Seymour, Jeremy C. Weiss |
| 2021 | AMIA | Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data. | Cheng Cheng, Helen Zhou, Jeremy C. Weiss, Zachary C. Lipton |
| 2021 | ICDM | Fair Decision-making Under Uncertainty. | Wenbin Zhang, Jeremy C. Weiss |
| 2021 | PAKDD | FARF: A Fair and Adaptive Random Forests Classifier. | Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl |
| 2020 | AIME | Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate. | Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss, George H. Chen |
| 2020 | AIME | Mortality Risk Score for Critically Ill Patients with Viral or Unspecified Pneumonia: Assisting Clinicians with COVID-19 ECMO Planning. | Helen Zhou, Cheng Cheng, Zachary C. Lipton, George H. Chen, Jeremy C. Weiss |
| 2019 | AMIA | Hypersphere clustering to characterize healthcare providers using prescriptions and procedures from Medicare claims data. | Nathanael Fillmore, Sergey Goryachev, Jeremy C. Weiss |
| 2018 | IJCAI | Bicluster phenotyping of healthcare providers, procedures, and prescriptions at scale with deep learning. | Nathanael Fillmore, Ansh Mehta, Jeremy C. Weiss |
| 2015 | AAAI | Learning to Reject Sequential Importance Steps for Continuous-Time Bayesian Networks. | Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr. |
| 2015 | AMIA | Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. | Jeremy C. Weiss, Finn Kuusisto, Kendrick Boyd, Jie Liu, David Page |
| 2013 | AAAI | Learning When to Reject an Importance Sample. | Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr. |
| 2012 | IAAI | Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records. | Jeremy C. Weiss, Sriraam Natarajan, Peggy L. Peissig, Catherine A. McCarty, David Page |